Journal of Medical Systems

, 37:9898 | Cite as

Smart Health Monitoring Systems: An Overview of Design and Modeling

Original Paper

Abstract

Health monitoring systems have rapidly evolved during the past two decades and have the potential to change the way health care is currently delivered. Although smart health monitoring systems automate patient monitoring tasks and, thereby improve the patient workflow management, their efficiency in clinical settings is still debatable. This paper presents a review of smart health monitoring systems and an overview of their design and modeling. Furthermore, a critical analysis of the efficiency, clinical acceptability, strategies and recommendations on improving current health monitoring systems will be presented. The main aim is to review current state of the art monitoring systems and to perform extensive and an in-depth analysis of the findings in the area of smart health monitoring systems. In order to achieve this, over fifty different monitoring systems have been selected, categorized, classified and compared. Finally, major advances in the system design level have been discussed, current issues facing health care providers, as well as the potential challenges to health monitoring field will be identified and compared to other similar systems.

Keywords

Smart health monitoring Remote patient monitoring Wearable health monitoring Mobile health monitoring 

References

  1. 1.
    Williams, J., Wireless in Healthcare: A Study Tracking the Use of RFID, Wireless Sensor Solutions, and Telemetry Technologies by Medical Device Manufacturers and Healthcare Providers. The FocalPoint Group, USA, 2004.Google Scholar
  2. 2.
    Tamura, T., Togawa, T., Ogawa, M., and Yoda, M., Fully automated health monitoring system in the home. Med. Eng. Phys. 20(8):573–579, 1998.CrossRefGoogle Scholar
  3. 3.
    Ohta, S., Nakamoto, H., Shinagawa, Y., and Tanikawa, T., A health monitoring system for elderly people living alone. J. Telemed. Telec. 8(3):151, 2002.CrossRefGoogle Scholar
  4. 4.
    Roine, R., Ohinmaa, A., and Hailey, D., Assessing telemedicine: a systematic review of the literature. Can. Med. Assoc. J. 165(6):765–71, 2001.Google Scholar
  5. 5.
    Lau, F., Kuziemsky, C., Price, M., and Gardner, J., A review on systematic reviews of health information system studies. JAMIA 17:637–645, 2010.Google Scholar
  6. 6.
    Brownsell, S., Bradley, D., Blackburn, S., Cardinaux, F., and Hawley, M. S., A systematic review of lifestyle monitoring technologies. J. Telemed. Telec. 17(4):185–189, 2011.CrossRefGoogle Scholar
  7. 7.
    Cardile, F., Iannizzotto, G., and F. La Rosa, A vision-based system for elderly patients monitoring. In Human System Interactions (HSI), 2010 3rd Conference on, 195–202 2010.Google Scholar
  8. 8.
    Taleb, T., Bottazzi, D., Guizani, M., and Nait-Charif, H., Angelah: a framework for assisting elders at home. IEEE J. Sel. Area. Comm. 27(4):480–494, 2009.CrossRefGoogle Scholar
  9. 9.
    Dong-Her, S., Hsiu-Sen, C., Binshan, L., and Shih-Bin, L., An Embedded Mobile ECG Reasoning System for Elderly Patients. IEEE Trans. Inf. Technol. Biomed. 14(3):854–865, 2010.CrossRefGoogle Scholar
  10. 10.
    Chung-Chih, L., Ming-Jang, C., Chun-Chieh, H., Ren-Guey, L., and Yuh-Show, T., Wireless Health Care Service System for Elderly With Dementia. IEEE Trans. Inf. Technol. Biomed. 10(4):696–704, 2006.CrossRefGoogle Scholar
  11. 11.
    Chung-Chih, L., Ping-Yeh, L., Po-Kuan, L., Guan-Yu, H., Wei-Lun, L., and Ren-Guey, L., A Healthcare Integration System for Disease Assessment and Safety Monitoring of Dementia Patients. IEEE Trans. Inf. Technol. Biomed. 12(5):579–586, 2008.CrossRefGoogle Scholar
  12. 12.
    Taub, D. M., Leeb, S. B., Lupton, E. C., Hinman, R. T., Zeisel, J., and Blackler, S., The Escort System: A Safety Monitor for People Living with Alzheimer's Disease. IEEE Pervasive Computing 10(2):68–77, 2011.CrossRefGoogle Scholar
  13. 13.
    Ho, C., and Weihua, Z., Bluetooth-enabled in-home patient monitoring system: Early detection of Alzheimer’s disease. IEEE Wirel. Commun. 17(1):74–79, 2010.CrossRefGoogle Scholar
  14. 14.
    Bor-Rong, C., Patel, S., Buckley, T., Rednic, R., McClure, D. J., Shih, L., Tarsy, D., Welsh, M., and Bonato, P., A Web-Based System for Home Monitoring of Patients With Parkinson’s Disease Using Wearable Sensors. IEEE Trans. Biomed. Eng. 58(3):831–836, 2011.CrossRefGoogle Scholar
  15. 15.
    Keijsers, N. L. W., Horstink, M. W. I. M., and Gielen, S. C. A. M., Online monitoring of dyskinesia in patients with Parkinson’s disease. IEEE Eng. Med. Biol. Mag. 22(3):96–103, 2003.CrossRefGoogle Scholar
  16. 16.
    Patel, S., Lorincz, K., Hughes, R., Huggins, N., Growdon, J., Standaert, D., Akay, M., Dy, J., Welsh, M., and Bonato, P., Monitoring Motor Fluctuations in Patients With Parkinson’s Disease Using Wearable Sensors. IEEE Trans. Inf. Technol. Biomed. 13(6):864–873, 2009.CrossRefGoogle Scholar
  17. 17.
    Yonglin, R., Pazzi, R. W. N., and Boukerche, A., Monitoring patients via a secure and mobile healthcare system. IEEE Wireless Communications 17(1):59–65, 2010.CrossRefGoogle Scholar
  18. 18.
    Naufal Bin Mansor, M., Yaacob, S., Nagarajan, R., and Hariharan, M., Patient monitoring in ICU under unstructured lighting condition. In Industrial Electronics & Applications (ISIEA), 2010 IEEE Symposium on, 608–611, 2010.Google Scholar
  19. 19.
    Wai Kit, W., Yen Chee, P., Chu Kiong, L., and Way Soong, L., Wireless webcam based omnidirectional health care surveillance system, In Computer Research and Development, 2010 Second International Conference on, 712–716, 2010.Google Scholar
  20. 20.
    JeongGil, K., Tia, G., Rothman, R., and Terzis, A., Wireless Sensing Systems in Clinical Environments: Improving the Efficiency of the Patient Monitoring Process. IEEE Eng. Med. Biol. Mag. 29(2):103–109, 2010.CrossRefGoogle Scholar
  21. 21.
    Xiaoxin, X., Mingguang, W., Cheng, D., Bin, S., and Jiangwei, Z., Outdoor wireless healthcare monitoring system for hospital patients based on ZigBee, In Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on, 549–554, 2010.Google Scholar
  22. 22.
    Junnila, S., Kailanto, H., Merilahti, J., Vainio, A. M., Vehkaoja, A., Zakrzewski, M., and Hyttinen, J., Wireless, Multipurpose In-Home Health Monitoring Platform: Two Case Trials. IEEE Trans. Inf. Technol. Biomed. 14(2):447–455, 2010.CrossRefGoogle Scholar
  23. 23.
    Rosati, R. J. Evaluation of remote monitoring in home health care. In eHealth, Telemedicine, and Social Medicine, 2009. eTELEMED09. International Conference on, 151–153, 2009.Google Scholar
  24. 24.
    Yongming, Y., Xiliang, L., and Yan, W., Immediate communication system for remote medical monitoring based on internet. In Automation Congress, 2008. WAC 2008. World, 1–5, 2008.Google Scholar
  25. 25.
    Safavi, A. A., Keshavarz-Haddad, A., Khoubani, S., Mosharraf-Dehkordi, S., Dehghani-Pilehvarani, A., and Tabei, F. S., A remote elderly monitoring system with localizing based on Wireless Sensor Network. In Computer Design and Applications (ICCDA), 2010 International Conference on, V2-553-V2-557, 2010.Google Scholar
  26. 26.
    Eleftheriadis, A., and Jacquin, A., Automatic face location detection and tracking for model-assisted coding of video teleconference sequences at low bit rates. Signal Process. Image Comm. 7(3):231–248, 1995.CrossRefGoogle Scholar
  27. 27.
    Rajagopalan, H., and Rahmat-Samii, Y., Ingestible RFID bio-capsule tag design for medical monitoring, In Antennas and Propagation Society International Symposium (APSURSI), 2010 IEEE, 1–4,, 2010.Google Scholar
  28. 28.
    Booth, P., Frisch, P. H., and Miodownik, S., Application of RFID in an Integrated Healthcare Environment, In Engineering in Medicine and Biology Society, 2006. EMBS06. 28th Annual International Conference of the IEEE, pp. 117–119, 2006.Google Scholar
  29. 29.
    Imhoff, M., and Kuhls, S., Alarm Algorithms in Critical Care Monitoring. International Anesthesia Research Society 102:1525–1537, 2006.Google Scholar
  30. 30.
    Otero, A., Félix, P., Barro, S., and Palacios, F., Addressing the flaws of current critical alarms: a fuzzy constraint satisfaction approach. Artificial Intelligence in Medicine 47(3):219–238, 2009.CrossRefGoogle Scholar
  31. 31.
    Zong, W., Moody, G. B., and Mark, R. G., Reduction of false arterial blood pressure alarms using signal quality assessment and relationships between the electrocardiogram and arterial blood pressure. Med. Biol. Eng. Comput. 42(5), 2006.Google Scholar
  32. 32.
    Lawless, S., Crying wolf: false alarms in a pediatric intensive care unit. Crit. Care Med. 22:981–5, 1994.CrossRefGoogle Scholar
  33. 33.
    Pandian, P. S., Mohanavelu, K., Safeer, K. P., Kotresh, T. M., Shakunthala, D. T., Gopal, P., and Padaki, V. C., Smart Vest: Wearable multi-parameter remote physiological monitoring system. Med. Eng. Phys. 30(4):466–477, 2008.CrossRefGoogle Scholar
  34. 34.
    López, G., Custodio, V., and Moreno, J. I., LOBIN: E-Textile and Wireless-Sensor-Network-Based Platform for Healthcare Monitoring in Future Hospital Environments. IEEE Trans. Inf. Technol. Biomed. 14(6):1446–1458, 2010.CrossRefGoogle Scholar
  35. 35.
    Pollonini, L., Rajan, N., Xu, S., Madala, S., and Dacso,C., A novel handheld device for use in remote patient monitoring of heart failure patients—Design and preliminary validation on healthy subjects. J. Med. Syst. 1–7, 2010.Google Scholar
  36. 36.
    Saito, M., Nakajima, K., Takano, C., Ohta, Y., Sugimoto, C., Ezoe, R., Sasaki, K., Hosaka, H., Ifukube, T., Ino, S., and Yamashita, K., An in-shoe device to measure plantar pressure during daily human activity. Med. Eng. Phys. 33(5):638–645, 2011.CrossRefGoogle Scholar
  37. 37.
    Mougiakakou, S. G., Bartsocas, C. S., Bozas, E., Chaniotakis, N., Iliopoulou, D., Kouris, I., Pavlopoulos, S., Prountzou, A., Skevofilakas, M., Tsoukalis, A., Varotsis, K., Vazeou, A., Zarkogianni, K., and Nikita, K. S., SMARTDIAB: A Communication and Information Technology Approach for the Intelligent Monitoring, Management and Follow-up of Type 1 Diabetes Patients. Information Technology in Biomedicine 14(3):622–633, 2010.CrossRefGoogle Scholar
  38. 38.
    Costin, H., Cehan, V., Rotariu, C., Morancea, O., Felea, V., Alexa, I., Andruseac, G., Costin, C., TELEMON—A complex system for real time telemonitoring of chronic patients and elderly people. In 4th European Conference of the International Federation for Medical and Biological Engineering. vol. 22, J. Sloten, et al., Eds., ed: Springer Berlin Heidelberg, 1002–1005, 2009Google Scholar
  39. 39.
    Raad M. W., and Yang, L. T., A ubiquitous smart home for elderly. In Advances in Medical, Signal and Information Processing, 2008. MEDSIP 2008. 4th IET International Conference on, 1–4, 2008.Google Scholar
  40. 40.
    Motoi, K., Ogawa, M., Ueno, H., Kuwae, Y., Ikarashi, A., Yuji, T., Higashi, Y., Tanaka, S., Fujimoto, T., Asanoi, H., and Yamakoshi, K. I., A fully automated health-care monitoring at home without attachment of any biological sensors and its clinical evaluation. In Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, 4323–4326, 2009.Google Scholar
  41. 41.
    Ishijima, M., and Togawa, T., Observation of electrocardiograms through tap water. Clin. Phys. Physiol. Meas. 10(2):171, 1989.CrossRefGoogle Scholar
  42. 42.
    Yong Gyu, L., Ko Keun, K., and Kwang Suk, P., ECG Recording on a Bed During Sleep Without Direct Skin-Contact. IEEE Trans. Biomed. Eng. 54(4):718–725, 2007.CrossRefGoogle Scholar
  43. 43.
    Ishida, S., Shiozawa, N., Fujiwara, Y., and Makikawa, M., Electrocardiogram Measurement during Sleep with Wearing Clothes Using Capacitively-Coupled Electrodes. In Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 2647–2650, 2007.Google Scholar
  44. 44.
    Ishijima, M., Cardiopulmonary monitoring by textile electrodes without subject-awareness of being monitored. Med. Biol. Eng. Comput. 35(6):685–690, 1997.CrossRefGoogle Scholar
  45. 45.
    Watanabe, K., Watanabe, T., Watanabe, H., Ando, H., Ishikawa, T., and Kobayashi, K., Noninvasive measurement of heartbeat, respiration, snoring and body movements of a subject in bed via a pneumatic method. IEEE Trans. Biomed. Eng. 52(12):2100–2107, 2005.CrossRefGoogle Scholar
  46. 46.
    Chow, P., Nagendra, G., Abisheganaden, J., and Wang, Y. T., Respiratory monitoring using an air-mattress system. Physiol. Meas. 21(3):345, 2000.CrossRefGoogle Scholar
  47. 47.
    Tamura, T., Zhou, J., Mizukami, H., and Togawa, T., A system for monitoring temperature distribution in bed and its application to the assessment of body movement. Physiol. Meas. 14(1):33, 1993.CrossRefGoogle Scholar
  48. 48.
    Tanaka, S., Nogawa, M., and Yamakoshi, K., Fully automatic system for monitoring blood pressure from a toilet-seat using the volume-oscillometric method. In Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the, 3939–3941, 2005.Google Scholar
  49. 49.
    Yamakoshi, K., Non-invasive cardiovascular hemodynamic measurements. In Sensors Applications, ed: Wiley-VCH Verlag GmbH & Co. KGaA, 107–160, 2008.Google Scholar
  50. 50.
    Yamakoshi, K., Unconstrained physiological monitoring in daily living for health care. Frontiers Med. Biol. Eng. 10(3):139–159, 2000.Google Scholar
  51. 51.
    Xin, Z., Wenxi, C., Nemoto, T., Kanemitsu, Y., Kitamura, K., Yamakoshi, K., and Daming, W., Real-Time Monitoring of Respiration Rhythm and Pulse Rate During Sleep. IEEE Trans. Biomed. Eng. 53(12):2553–2563, 2006.CrossRefGoogle Scholar
  52. 52.
    Arcelus, A., Jones, M. H., Goubran, R., and Knoefel, F., Integration of smart home technologies in a health monitoring system for the elderly. In Advanced Information Networking and Applications Workshops, 2007, AINAW07. 21st International Conference on, 820–825, 2007.Google Scholar
  53. 53.
    Redondi, A., Tagliasacchi, M., Cesana, M., Borsani, L., Tarri, x, P. o, and F. Salice, LAURA-LocAlization and ubiquitous monitoring of patients for health care support. In Personal, indoor and mobile radio communications workshops (PIMRC Workshops), 2010 IEEE 21st International Symposium on, 218–222, 2010.Google Scholar
  54. 54.
    Khandoker, A. H., Karmakar, C. K., and Palaniswami, M., Comparison of pulse rate variability with heart rate variability during obstructive sleep apnea. Med. Eng. Phys. 33(2):204–209, 2011.CrossRefGoogle Scholar
  55. 55.
    Label, L. S., Dementia facts and statistics, the national center for health statistics and the center for disease control, 2009.Google Scholar
  56. 56.
    Masud, T., and Morris, R. O., Epidemiology of falls. Age and Ageing 30(4):3–7, 2001.CrossRefGoogle Scholar
  57. 57.
    Stevens, J. A., Corso, P. S., Finkelstein, E. A., and Miller, T. R., The costs of fatal and non-fatal falls among older adults. Injury Prevention 12(5):290–295, 2006.CrossRefGoogle Scholar
  58. 58.
    Greene, B. R., Donovan, A. O., Romero-Ortuno, R., Cogan, L., Ni Scanaill, C., and Kenny, R. A., Quantitative Falls Risk Assessment Using the Timed Up and Go Test. IEEE Trans. Biomed. Eng. 57(12):2918–2926, 2010.CrossRefGoogle Scholar
  59. 59.
    Mathias, S., Nayak, U., and Isaacs, B., Balance in elderly patients: the “get-up and go” test. Arch. Phys. Med. Rehabil. 67(6):387–9, 1986.Google Scholar
  60. 60.
    Berg, K., Measuring balance in the elderly: preliminary development of an instrument. Physiotherapy Canada 41(6):304–311, 1989.CrossRefGoogle Scholar
  61. 61.
    Estudillo-Valderrama, M. A., Roa, L. M., Reina-Tosina, J., and Naranjo-Hernandez, D., Design and Implementation of a Distributed Fall Detection System-Personal Server. IEEE Trans. Inf. Technol. Biomed. 13(6):874–881, 2009.CrossRefGoogle Scholar
  62. 62.
    Pantelopoulos, A., and Bourbakis, N. G., Prognosis-A Wearable Health-Monitoring System for People at Risk: Methodology and Modeling. IEEE Trans. Inf. Technol. Biomed. 14(3):613–621, 2010.CrossRefGoogle Scholar
  63. 63.
    Gabriel, D. A., Christie, A., Inglis, J. G., and Kamen, G., Experimental and modelling investigation of surface EMG spike analysis. Medical Engineering & Physics 33(4):427–437, 2011.CrossRefGoogle Scholar
  64. 64.
    Guo, J.-Y., Zheng, Y.-P., Xie, H.-B., and Chen, X., Continuous monitoring of electromyography (EMG), mechanomyography (MMG), sonomyography (SMG) and torque output during ramp and step isometric contractions. Medical Engineering & Physics 32(9):1032–1042, 2010.CrossRefGoogle Scholar
  65. 65.
    Chan, V., Ray, P., and Parameswaran, N., Mobile e-Health monitoring: an agent-based approach. IET Commun. 2(2):223–230, 2008.CrossRefGoogle Scholar
  66. 66.
    Hande, A., Polk, T., Walker, W., and Bhatia, D., Self-Powered Wireless Sensor Networks for Remote Patient Monitoring in Hospitals. Sensors 6(9):1102–1117, 2006.CrossRefGoogle Scholar
  67. 67.
    Hiromichi, M., Hidekuni, O., Shingo, M., Yoshiharu, Y., and Morton, C. W., A daily living activity remote monitoring system for solitary elderly people. 33rd Annual International Conference of the IEEE EMBS, Boston, Massachusetts, 2011.Google Scholar
  68. 68.
    Apiletti, D., Baralis, E., Bruno, G., and Cerquitelli, T., Real-Time Analysis of Physiological Data to Support Medical Applications. IEEE Trans. Inf. Technol. Biomed. 13(3):313–321, 2009.CrossRefGoogle Scholar
  69. 69.
    Takano, C., and Ohta, Y., Heart rate measurement based on a time-lapse image. Med. Eng. Phys. 29(8):853–857, 2007.CrossRefGoogle Scholar
  70. 70.
    McAdams, E., Krupaviciute, A., Gehin, C., Grenier, E., Massot, B., Dittmar, A., Rubel, P., and Fayn, J., Wearable Sensor Systems: The Challenges. 33rd Annual International Conference of the IEEE EMBS, Boston, Massachusetts, 2011.Google Scholar
  71. 71.
    Ying, Z., and Hannan, X., Bluetooth-Based Sensor Networks for Remotely Monitoring the Physiological Signals of a Patient. IEEE Trans. Inf. Technol. Biomed. 13(6):1040–1048, 2009.CrossRefGoogle Scholar
  72. 72.
    Basilakis, J., Lovell, N. H., Redmond, S. J., and Celler, B. G., Design of a Decision-Support Architecture for Management of Remotely Monitored Patients. IEEE Trans. Inf. Technol. Biomed. 14(5):1216–1226, 2010.CrossRefGoogle Scholar
  73. 73.
    Tamura, T., Mizukura, I., Tatsumi, H., and Kimura, Y., Is the home health care monitoring effective? In Information Technology and Applications in Biomedicine, 2009. ITAB 2009. 9th International Conference on, 1–4, 2009.Google Scholar
  74. 74.
    Hairong, Y., Hongwei, H., Youzhi, X., and Gidlund, M., Wireless sensor network based E-health system-Implementation and experimental results. IEEE Trans. Consum. Electron. 56(4):2288–2295, 2010.CrossRefGoogle Scholar
  75. 75.
    Yoshizawa, M., Yambe, T., Konno, S., Saijo, Y., Sugita, N., Sugai, T. K., Abe, M., Sonobe, T., Katahira, Y., and Nitta, S., A mobile communications system for home-visit medical services: The Electronic Doctor's Bag. In Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE, 5496–5499, 2010.Google Scholar
  76. 76.
    Gargiulo, G., Bifulco, P., Calvo, R. A., Cesarelli, M., Jin, C., and van Schaik, A., Mobile biomedical sensing with dry electrodes. In Intelligent Sensors, Sensor Networks and Information Processing, 2008. ISSNIP 2008. International Conference on, 261–266, 2008.Google Scholar
  77. 77.
    Faria, S., Fernandes, T. R., and Perdigoto, F. S., Mobile web server for elderly people monitoring. In Consumer Electronics, 2008. ISCE 2008. IEEE International Symposium on, 2008, pp. 1–4.Google Scholar
  78. 78.
    Logan, A. G., McIsaac, W. J., Tisler, A., Irvine, M. J., Saunders, A., Dunai, A., Rizo, C. A., Feig, D. S., Hamill, M., Trudel, M., and Cafazzo, J. A., Mobile Phone-Based Remote Patient Monitoring System for Management of Hypertension in Diabetic Patients. Am. J. Hypertens. 20(9):942–948, 2007.CrossRefGoogle Scholar
  79. 79.
    Tatara, E., and Cinar, A., Interpreting ECG data by integrating statistical and artificial intelligence tools. IEEE Eng Med Biol Mag 21(1):36–41, 2002.CrossRefGoogle Scholar
  80. 80.
    Hernandez, A. I., Mora, F., Villegas, M., Passariello, G., and Carrault, G., Real-time ECG transmission via Internet for nonclinical applications. IEEE Trans. Inf. Technol. Biomed. 5(3):253–257, 2001.CrossRefGoogle Scholar
  81. 81.
    Rashid, R. A., Rahim, M. R. A., Sarijari, M. A., and Mahalin, N., Design and implementation of Wireless Biomedical Sensor Networks for ECG home health monitoring. In Electronic Design, 2008. ICED 2008. International Conference on, 1–4, 2008.Google Scholar
  82. 82.
    Garcia, J., Martinez, I., Sornmo, L., Olmos, S., Mur, A., and Laguna, P., Remote processing server for ECG-based clinical diagnosis support. IEEE Trans. Inf. Technol. Biomed. 6(4):277–284, 2002.CrossRefGoogle Scholar
  83. 83.
    Wan-Young, C., Seung-Chul, L., and Sing-Hui, T., WSN based mobile u-healthcare system with ECG, blood pressure measurement function. In Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE, 1533–1536, 2008.Google Scholar
  84. 84.
    Boukerche, A., and Yonglin, R., A secure mobile healthcare system using trust-based multicast scheme. IEEE J. Sel. Area Comm. 27(4):387–399, 2009.CrossRefGoogle Scholar
  85. 85.
    Al Ameen, M., Liu, J., and Kwak, K., Security and Privacy Issues in Wireless Sensor Networks for Healthcare Applications, Journal of Medical Systems. 1–9, 2010.Google Scholar
  86. 86.
    Anagnostaki, A. P., Pavlopoulos, S., Kyriakou, E., and Koutsouris, D., A novel codification scheme based on the “VITAL” and “DICOM” standards for telemedicine applications. IEEE Trans. Biomed. Eng. 49(12):1399–1411, 2002.CrossRefGoogle Scholar
  87. 87.
    Hinrichs, H., Feistner, H., and Heinze, H. J., A trend-detection algorithm for intraoperative EEG monitoring. Medical Engineering & Physics 18(8):626–631, 1996.CrossRefGoogle Scholar
  88. 88.
    Panescu, D., Emerging Technologies [wireless communication systems for implantable medical devices]. Engineering in Medicine and Biology Magazine, IEEE 27(2):96–101, 2008.CrossRefGoogle Scholar
  89. 89.
    Kumar, S., Kambhatla, K., Hu, F., Lifson, M., and Xiao, Y., Ubiquitous computing for remote cardiac patient monitoring: a survey. Int. J. Telemedicine Appl. 1–19, 2008.Google Scholar
  90. 90.
    Oleshchuk, V., and Fensli, R., Remote Patient Monitoring Within a Future 5 G Infrastructure. Wirel. Pers. Commun. 57(3):431–439, 2011.CrossRefGoogle Scholar
  91. 91.
    William, R. H., and Michael, M. W., Accuracy of Data in Computer-based Patient Records. JAMIA 4:342–355, 1997.Google Scholar
  92. 92.
    Pantelopoulos, A., and Bourbakis, N. G., A Survey on Wearable Sensor-Based Systems for Health Monitoring and Prognosis. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 40(1):1–12, 2010.CrossRefGoogle Scholar
  93. 93.
    Kulkarni, P., and Ozturk, Y., mPHASiS: Mobile patient healthcare and sensor information system. J. Netw. Comput. Appl. 34(1):402–417, 2011.CrossRefGoogle Scholar
  94. 94.
    Sankari, Z., and Adeli, H., HeartSaver: A mobile cardiac monitoring system for auto-detection of atrial fibrillation, myocardial infarction, and atrio-ventricular block. Com. Biol. Med. 41(4):211–220, 2011.CrossRefGoogle Scholar
  95. 95.
    Bitterman, N., Design of medical devices–A home perspective. Eur. J. Intern. Med. 22(1):39–42, 2011.CrossRefGoogle Scholar
  96. 96.
    Cho, H.-S., Koo, S.-M., Lee, J., Cho, H., Kang, D.-H., Song, H.-Y., Lee, J.-W., Lee, K.-H., and Lee, Y.-J., Heart Monitoring Garments Using Textile Electrodes for Healthcare Applications. J. Med. Syst. 35(2):189–201, 2011.CrossRefGoogle Scholar
  97. 97.
    Chang, H.-T., Chung, C.-G., and M.-W. Chen, An e-caring chair for physiological signal measurement and recording. Med. Eng. Phys., vol. In Press, Corrected Proof, 2011.Google Scholar
  98. 98.
    Chin-Teng, L., Kuan-Cheng, C., Chun-Ling, L., Chia-Cheng, C., Shao-Wei, L., Shih-Sheng, C., Bor-Shyh, L., Hsin-Yueh, L., Ray-Jade, C., Yuan-Teh, L., and Li-Wei, K., An Intelligent Telecardiology System Using a Wearable and Wireless ECG to Detect Atrial Fibrillation. IEEE Trans. Inf. Technol. Biomed. 14(3):726–733, 2010.CrossRefGoogle Scholar
  99. 99.
    Coyle, S., King-Tong, L., Moyna, N., O’Gorman, D., Diamond, D., Di Francesco, F., Costanzo, D., Salvo, P., Trivella, M. G., De Rossi, D. E., Taccini, N., Paradiso, R., Porchet, J. A., Ridolfi, A., Luprano, J., Chuzel, C., Lanier, T., Revol-Cavalier, F., Schoumacker, S., Mourier, V., Chartier, I., Convert, R., De-Moncuit, H., and Bini, C., BIOTEX-Biosensing Textiles for Personalised Healthcare Management. IEEE Trans. Inf. Technol. Biomed. 14(2):364–370, 2010.CrossRefGoogle Scholar
  100. 100.
    Di Rienzo, M., Meriggi, P., Rizzo, F., Castiglioni, P., Lombardi, C., Ferratini, M., and Parati, G., Textile Technology for the Vital Signs Monitoring in Telemedicine and Extreme Environments. IEEE Trans. Inf. Technol. Biomed. 14(3):711–717, 2010.CrossRefGoogle Scholar
  101. 101.
    Fei, D.-Y., Zhao, X., Boanca, C., Hughes, E., Bai, O., Merrell, R., and Rafiq, A., A biomedical sensor system for real-time monitoring of astronauts’ physiological parameters during extra-vehicular activities. Comput. Biol. Med. 40(7):635–642, 2010.CrossRefGoogle Scholar
  102. 102.
    Zimu, L., Guodong, F., Fenghe, L., Dong, J.Q., Kamoua, R., and Tang, W., Wireless health monitoring system. In Applications and Technology Conference (LISAT), 2010 Long Island Systems, pp. 1–4, 2010.Google Scholar
  103. 103.
    Watthanawisuth, N., Lomas, T., Wisitsoraat, A., and Tuantranont, A., Wireless wearable pulse oximeter for health monitoring using ZigBee wireless sensor network. In Electrical Engineering/Electronics Computer Telecommunications and Information Technology (ECTI-CON), 2010 International Conference on, 575–579, 2010.Google Scholar
  104. 104.
    Shin, W., Cha, Y., and Yoon, G., ECG/PPG Integer Signal Processing for a Ubiquitous Health Monitoring System. J. Med. Syst. 34(5):891–898, 2010.CrossRefGoogle Scholar
  105. 105.
    Yoo, J., Long, Y., Seulki, L., Hyejung, K., and Hoi-Jun, Y., A Wearable ECG Acquisition System With Compact Planar-Fashionable Circuit Board-Based Shirt. IEEE Trans. Inf. Technol. Biomed. 13(6):897–902, 2009.CrossRefGoogle Scholar
  106. 106.
    Alesanco, A., and Garci, J., Clinical Assessment of Wireless ECG Transmission in Real-Time Cardiac Telemonitoring. IEEE Trans. Inf. Technol. Biomed. 14(5):1144–1152, 2010.CrossRefGoogle Scholar
  107. 107.
    Atoui, H., Fayn, J., and Rubel, P., A Novel Neural-Network Model for Deriving Standard 12-Lead ECGs From Serial Three-Lead ECGs: Application to Self-Care. IEEE Trans. Inf. Technol. Biomed. 14(3):883–890, 2010.CrossRefGoogle Scholar
  108. 108.
    Bianchi, A. M., Mendez, M. O., and Cerutti, S., Processing of Signals Recorded Through Smart Devices: Sleep-Quality Assessment. IEEE Trans. Inf. Technol. Biomed. 14(3):741–747, 2010.CrossRefGoogle Scholar
  109. 109.
    Jourand, P., De Clercq, H., Corthout, R., and Puers, R., Textile Integrated Breathing and ECG Monitoring System. Procedia Chemistry 1(1):722–725, 2009.CrossRefGoogle Scholar
  110. 110.
    Kim, Y., Baek, H., Kim, J., Lee, H., Choi, J., and Park, K., Helmet-based physiological signal monitoring system. Eur. J. Appl. Physiol. 105(3):365–372, 2009.CrossRefGoogle Scholar
  111. 111.
    Lee, Y.-D., and Chung, W.-Y., Wireless sensor network based wearable smart shirt for ubiquitous health and activity monitoring. Sensor. Actuator. B Chem. 140(2):390–395, 2009.CrossRefGoogle Scholar
  112. 112.
    Tay, F. E. H., Guo, D. G., Xu, L., Nyan, M. N., and Yap, K. L., MEMSWear-biomonitoring system for remote vital signs monitoring. J. Frankl. Inst. 346(6):531–542, 2009.MATHCrossRefGoogle Scholar
  113. 113.
    Sufi, F., Qiang, F., Khalil, I., and Mahmoud, S. S., Novel methods of faster cardiovascular diagnosis in wireless telecardiology. IEEE J. Sel. Area. Comm. 27(4):537–552, 2009.CrossRefGoogle Scholar
  114. 114.
    Steele, R., Lo, A., Secombe, C., and Wong, Y. K., Elderly persons’ perception and acceptance of using wireless sensor networks to assist healthcare. Int. J. Med. Informat. 78(12):788–801, 2009.CrossRefGoogle Scholar
  115. 115.
    Shih-Lun, C., Ho-Yin, L., Chiung-An, C., Hong-Yi, H., and Ching-Hsing, L., Wireless Body Sensor Network With Adaptive Low-Power Design for Biometrics and Healthcare Applications. IEEE Syst. J. 3(4):398–409, 2009.CrossRefGoogle Scholar
  116. 116.
    Merritt, C. R., Nagle, H. T., and Grant, E., Fabric-Based Active Electrode Design and Fabrication for Health Monitoring Clothing. IEEE Trans. Inf. Technol. Biomed. 13(2):274–280, 2009.CrossRefGoogle Scholar
  117. 117.
    Wu, W. H., Bui, A. A. T., Batalin, M. A., Au, L. K., Binney, J. D., and Kaiser, W. J., MEDIC: Medical embedded device for individualized care. Artif. Intell. Med. 42(2):137–152, 2008.CrossRefGoogle Scholar
  118. 118.
    Kailanto, H., Hyvarinen, E., and Hyttinen, J., Mobile ECG measurement and analysis system using mobile phone as the base station, 12–14, 2008.Google Scholar
  119. 119.
    Heilman, K., Handelman, M., Lewis, G., and Porges, S., Accuracy of the StressEraser in the Detection of Cardiac Rhythms. Appl. Psychophysiol. Biofeedback. 33(2):83–89, 2008.CrossRefGoogle Scholar
  120. 120.
    Geng, Y., Jian, C., Ying, C., Tenhunen, H., and Li-Rong, Z., A novel wearable ECG monitoring system based on active-cable and intelligent electrodes. In e-health Networking, Applications and Services, 2008. HealthCom 2008. 10th International Conference on, 156–159, 2008.Google Scholar
  121. 121.
    Yanbiao, Z., Cunxi, X., and Zhaohua, L., Intelligent analysis system in time series of smart health home on-line monitoring data. In Control and Automation, 2007. ICCA 2007. IEEE International Conference on, 1785–1790, 2007.Google Scholar
  122. 122.
    Ren-Guey, L., Kuei-Chien, C., Chun-Chieh, H., and Chwan-Lu, T., A Mobile Care System With Alert Mechanism. IEEE Trans. Inf. Technol. Biomed. 11(5):507–517, 2007.CrossRefGoogle Scholar
  123. 123.
    Logan, A. G., McIsaac, W. J., Tisler, A., Irvine, M. J., Saunders, A., Dunai, A., Rizo, C. A., Feig, D. S., Hamill, M., and Trudel, M., Mobile phone-based remote patient monitoring system for management of hypertension in diabetic patients. Am. J. Hypertens. 20(9):942–948, 2007.CrossRefGoogle Scholar
  124. 124.
    Lee, G., Tsai, C., Griswold, W. G., Raab, F., and Patrick, K., PmEB: a mobile phone application for monitoring caloric balance, 1013–1018, 2006.Google Scholar
  125. 125.
    Okumura, F., Kubota, A., Hatori, Y., Matsuo, K., Hashimoto, M., and Koike, A., A study on biometric authentication based on arm sweep action with acceleration sensor, 219–222, 2006.Google Scholar
  126. 126.
    Finkelstein, S. M., Speedie, S. M., and Potthoff, S., Home telehealth improves clinical outcomes at lower cost for home healthcare. Telemed. J. e Health 12(2):128–136, 2006.CrossRefGoogle Scholar
  127. 127.
    Yu, V. L., and Madoff, L. C., ProMED-mail: an early warning system for emerging diseases. Clin. Infect. Dis. 39(2):227, 2004.CrossRefGoogle Scholar
  128. 128.
    Shieh, J. S., Linkens, D. A., and Peacock, J. E., A computer screen-based simulator for hierarchical fuzzy logic monitoring and control of depth of anaesthesia. Math. Comput. Simul. 67(3):251–265, 2004.MathSciNetMATHCrossRefGoogle Scholar
  129. 129.
    Mendoza G. G., and Tran, B. Q., In-home wireless monitoring of physiological data for heart failure patients. In Engineering in medicine and biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint, vol.3. 1849–1850, 2002.Google Scholar
  130. 130.
    Sneha, S., and Varshney, U., Enabling ubiquitous patient monitoring: Model, decision protocols, opportunities and challenges. Decis. Support. Syst. 46(3):606–619, 2009.CrossRefGoogle Scholar
  131. 131.
    Varady, P., Benyo, Z., and Benyo, B., An open architecture patient monitoring system using standard technologies. IEEE Trans. Inf. Technol. Biomed. 6(1):95–98, 2002.CrossRefGoogle Scholar
  132. 132.
    Jaesoon, C., Park, J. W., Jinhan, C., and Min, B. G., An intelligent remote monitoring system for artificial heart. IEEE Trans. Inf. Technol. Biomed. 9(4):564–573, 2005.CrossRefGoogle Scholar
  133. 133.
    Magni, P., and Bellazzi, R., A stochastic model to assess the variability of blood glucose time series in diabetic patients self-monitoring. IEEE Trans. Biomed. Eng. 53(6):977–985, 2006.CrossRefGoogle Scholar
  134. 134.
    Mirza, M., Gholam Hosseini, H., and Harrison, M., Fuzzy Logic-based System for Anaesthesia Monitoring. 32nd Annual International Conference of the IEEE EMBC, Buenos Aires, Argentina, 2010.Google Scholar
  135. 135.
    Gohil, B., GholamhHosseini, H., Harrison, M. J., Lowe, A., and Al-Jumaily, A., Intelligent monitoring of critical pathological events during anesthesia. In 29th Annual International Conference of the IEEE in Engineering in Medicine and Biology Society (EMBS), 4343–4346, 2007.Google Scholar
  136. 136.
    Lowe, A., and Harrison, M. J., Computer-enhanced diagnosis of malignant hyperpyrexia. Anaesthesia and Intensive Care [NLM-MEDLINE] 27(1):41, 1999.Google Scholar
  137. 137.
    Harrison, M. J., Kluger, M. T., and Robertson, N. N., The relationship between change in blood pressure, blood pressure and time. Anaesthesia 55:385–387, 2000.CrossRefGoogle Scholar
  138. 138.
    Teunissen, L., Klewer, J., De Haan, A., De Koning, J., and Daanen, H., Non-invasive continuous core temperature measurement by zero heat flux. Physiol. Meas. 32(5):559, 2011.CrossRefGoogle Scholar
  139. 139.
    Harrison, M. J., and Connor, C. W., Statistics-based alarms from sequential physiological measurements. Anaesthesia 62(10):1015–1023, 2007.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Department of Electrical and Electronic EngineeringSchool of Engineering, Auckland University of TechnologyAucklandNew Zealand

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